Association of Interfacility Helicopter versus Ground Ambulance Transport and in-Hospital Mortality among Trauma Patients

Rise of long-distance urology transfer during the COVID-19 pandemic: Identifying factors to enhance transfers of care efficiency and clinical outcomes

OBJECTIVE

The objective of this study is to identify variables associated with clinical outcomes after urologic transfers before and during the COVID pandemic.

METHODS

After IRB approval, a retrospective chart review was performed on adult patients transferred to our institution from 01/01/2018 to 12/31/2019 ("pre-COVID") and from 01/02/2020 to 12/31/2022 ("COVID"). We identified demographics, origin hospitals, ICD-10 pre- and post-transfer diagnoses, distance of transfer, and post-transfer CPT codes.

RESULTS

During the study period, our adult urology service accepted 160 transfers with a mean patient age of 71 years. A total of 49/160 (30%) of subjects made up the "pre-COVID" cohort and 111/160 (70%) made up the "COVID" cohort. There were 11/111 (10%) transfers of >100 miles in the COVID period but 0/49 in the pre-COVID period (p = 0.02). Patients from the COVID period waited on average 1.2 days longer for a procedure after transfer compared to pre-COVID period (p = 0.03). The time until a patient's surgical procedure after transfer was a significant predictor of length of stay > 5 days (OR 1.91, CI 1.43 - 2.58, p < 0.01). Different diagnosis upon re-evaluation after transfer was associated with a decreased rate of subsequent readmission (OR 0.30, CI 0.09-0.97, p = 0.05).

CONCLUSIONS

Long-distance transfer, even >100 miles (which we termed "mega-transfers"), was a new pandemic-related phenomenon at our institution. Delays in definitive care and changes in diagnoses after transfer were associated with readmission and length of stay. Our findings illustrate the importance of inter-institutional communication, diagnostic accuracy, and post discharge planning when managing transfer patients.

Aeromedical Transport for Critically Ill Patients

Aeromedical transport (AMT) is an integral part of healthcare systems worldwide. In this article, the personnel and equipment required, associated safety considerations, and evidence supporting the use of AMT is reviewed, with an emphasis on helicopter emergency medical services (HEMS). Indications for HEMS as guideded by the Air Medical Prehospital Triage Score are presented. Lastly, physiologic considerations, which are important to both AMT crews and receiving clinicians, are reviewed.

Correlation between the 72-hour fatality ratios and out-of-hospital cardiac arrest ratios in patients with extremely high outlier values of 57 laboratory test items: A single-center retrospective inception cohort study

The association between extremely high outlier values (EHOV) of laboratory test items (LTIs) and short-term prognosis or out-of-hospital cardiac arrest (OHCA) remains unclear. This retrospective study investigated the correlation between 72-hour fatality ratios and OHCA ratios in patients with the top 100 EHOV of 57 LTIs without focusing on the disease group and which test items were predictors of 72-hour fatality. This single-center retrospective inception cohort study enrolled patients aged ≥ 18 years who underwent any combination of laboratory tests at the Saitama Medical Center, Japan between January 1, 2008, and December 31, 2013. The primary outcome was the correlation between the 72-hour fatality ratios and OHCA ratios in patients with the top 100 EHOV for 57 LTIs without focusing on the disease group. The LTIs included hematology, blood chemistry, erythrocyte sedimentation, blood coagulation, and arterial blood gas test results. The secondary outcome was which of the 57 LTIs with the top 100 EHOV were more likely to associate with the 72-hour fatality. We evaluated the correlation between the 72-hour fatality ratios and the OHCA ratios for each laboratory test item using the Passing-Bablok regression method. The 72-hour fatality ratios for the top 100 EHOV of 57 LTIs were significantly positively correlated with the OHCA ratios. The regression coefficient of the regression line was 0.394, and the correlation coefficient (95% confidence interval) was 0.644 (0.458-0.775, P < .001). These 72-hour fatality ratios tended to be lower than the OHCA ratios. The top 100 EHOV of 13 LTIs including total bilirubin, direct bilirubin, C-reactive protein, base excess, bicarbonate ion, creatine kinase, uric acid, partial pressure of oxygen, sodium, chloride, blood urea nitrogen, aspartate aminotransferase, and lactate dehydrogenase had 72-hour fatality ratios that were above the upper limit of the linear confidence region of the regression line, with higher 72-hour fatality ratios than the OHCA ratios. The 72-hour fatality ratios for the top 100 EHOV of 57 LTIs tended to be lower than the OHCA ratios. The top 100 EHOV of these 13 LTIs were found to be more likely to associate with 72-hour fatality than OHCA.

Predicting 72-h mortality in patients with extremely high random plasma glucose levels: A case-controlled cross-sectional study

The risk factors associated with 72-hours mortality in patients with extremely high levels of random plasma glucose (RPG) remain unclear.To explore the risk factors predictive of 72-hours mortality in patients with extremely high RPG under heterogenos pathophysiological conditions.Retrospective, single-center, case-controlled cross-sectional study.University teaching hospital.Adults over age 18 were selected from the medical records of patients at the Saitama Medical Center, Japan, from 2004 to 2013.Extremely high RPG (≥500 mg/dl).Mortality at 72 hours following the RPG test, regardless of hospitalization or in an outpatient setting. Multivariate logistic regression analysis was performed with adjustment for age, sex, body mass index (BMI), and RPG level. The final prediction model was built using the logistic regression model with a higher C-statistic, specificity, and sensitivity.A total of 351 patients with RPG ≥500 mg/dl were identified within the 10-year period. The 72-hours mortality rate was 16/351 (4.6%). The C-statistics of the 72-hours mortality prediction model with serum albumin (ALB) and creatine kinase (CK) was 0.856. The probability of 72-hours mortality was calculated as follows: 1/[1 + exp (-5.142 + 0.901log (CK) -1.087 (ALB) + 0.293 (presence (1) or absence (0) of metastatic solid tumor)]. The sensitivity and specificity of this model was 75.5%.The independent risk factors associated with 72-hours mortality in patients with RPG ≥500 mg/dl are hypoalbuminemia, elevated CK, and presence of a metastatic solid tumour. Further research is needed to understand the mechanisms and possible interventions to prevent mortality associated with extremely high RPG.